{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T03:15:41Z","timestamp":1758078941834,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686196","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,16]]},"abstract":"<jats:p>Legal queries are often expressed in unstructured, ambiguous, or noisy natural language, which poses significant challenges for accurate information retrieval. This paper presents a comprehensive framework for legal question answering that integrates semantic technologies\u2014including an ontology platform, knowledge graph, and large language models (LLMs)\u2014to improve question understanding and response accuracy. We propose a multi-step pre-processing pipeline that standardizes legal questions using spelling correction, abbreviation expansion, syntactic restructuring, and semantic summarization supported by LLMs. Besides, a query system is designed that maps pre-processed questions into graph-based representations and performs subgraph matching over a legal knowledge graph. The system is evaluated on real-world legal questions collected from online forums covering traffic law and social insurance. The results show that the proposed approach achieves a high semantic similarity score (avg. cosine similarity of 0.9078 after standardization) and outperforms baseline LLMs like ChatGPT and Gemini in query accuracy (up to 82.25% in certain question categories). These findings highlight the effectiveness of combining LLMs and semantic structures for robust legal information retrieval.<\/jats:p>","DOI":"10.3233\/faia250543","type":"book-chapter","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:19:55Z","timestamp":1758028795000},"source":"Crossref","is-referenced-by-count":0,"title":["Extracting Core Meaning from Legal Queries Using Semantic Technologies"],"prefix":"10.3233","author":[{"given":"Dang V.","family":"Dung","sequence":"first","affiliation":[{"name":"University of Information Technology, Ho Chi Minh city, Vietnam"},{"name":"Vietnam National University, Ho Chi Minh city, Vietnam"}]},{"given":"Vuong T.","family":"Pham","sequence":"additional","affiliation":[{"name":"University of Science, Ho Chi Minh city, Vietnam"},{"name":"Vietnam National University, Ho Chi Minh city, Vietnam"},{"name":"Sai Gon University, Ho Chi Minh city, Vietnam"}]},{"given":"Huong","family":"Tran","sequence":"additional","affiliation":[{"name":"University of Information Technology, Ho Chi Minh city, Vietnam"},{"name":"Vietnam National University, Ho Chi Minh city, Vietnam"}]},{"given":"Minh N.","family":"Phan","sequence":"additional","affiliation":[{"name":"Sai Gon University, Ho Chi Minh city, Vietnam"}]},{"given":"Huy","family":"Huynh","sequence":"additional","affiliation":[{"name":"Sai Gon University, Ho Chi Minh city, Vietnam"}]},{"given":"Hien D.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"University of Information Technology, Ho Chi Minh city, Vietnam"},{"name":"Vietnam National University, Ho Chi Minh city, Vietnam"},{"name":"Computer Science Department, New Mexico State University, USA"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250543","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:19:55Z","timestamp":1758028795000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250543"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,16]]},"ISBN":["9781643686196"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250543","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,16]]}}}